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Technical efficiency in firm games with constant returns to scale and $$\alpha $$-returns to scale

Author

Listed:
  • Walter Briec

    (LAMPS - LAboratoire de Modélisation Pluridisciplinaire et Simulations - UPVD - Université de Perpignan Via Domitia)

  • Marc Dubois

    (UNIMES - Nîmes Université, CUFR - Centre Universitaire de Formation et de Recherche de Mayotte (CUFR))

  • Stéphane Mussard

    (CHROME - Détection, évaluation, gestion des risques CHROniques et éMErgents (CHROME) - Nîmes Université - UNIMES - Nîmes Université)

Abstract

Under a technology based on the generalized mean of inputs and outputs with constant returns to scale (CRS), the firms have incentive to merge (in a firm game) in order to improve their technical efficiency. A directional complementarity property in inputs and in outputs is introduced. It is shown that the core of the firm game is non-void whenever the aggregate technology of each coalition exhibits complementarity in outputs and CRS. In the case of $$\alpha $$ α -returns to scale, the firms have incentive to merge (improvement of technical efficiency) when there are both directional complementarity in inputs and in outputs.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Walter Briec & Marc Dubois & Stéphane Mussard, 2021. "Technical efficiency in firm games with constant returns to scale and $$\alpha $$-returns to scale," Post-Print hal-03264193, HAL.
    • Handle: RePEc:hal:journl:hal-03264193
    DOI: 10.1007/s10479-021-04056-6
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    Cited by:

    1. Tsionas, Mike & Parmeter, Christopher F. & Zelenyuk, Valentin, 2023. "Bayesian Artificial Neural Networks for frontier efficiency analysis," Journal of Econometrics, Elsevier, vol. 236(2).
    2. Valentin Zelenyuk, 2024. "Aggregation in efficiency and productivity analysis: a brief review with new insights and justifications for constant returns to scale," Journal of Productivity Analysis, Springer, vol. 62(3), pages 321-334, December.

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